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Design flood estimation at ungauged catchments using index flood method and quantile regression technique: a case study for South East Australia

Author

Listed:
  • Amir Zalnezhad

    (Western Sydney University)

  • Ataur Rahman

    (Western Sydney University)

  • Farhad Ahamed

    (Western Sydney University)

  • Mehdi Vafakhah

    (Tarbiat Modares University)

  • Bijan Samali

    (Western Sydney University)

Abstract

Flood is one of the worst natural disasters, which causes the damage of billions of dollars each year globally. To reduce the flood damage, we need to estimate design floods accurately, which are used in the design and operation of water infrastructure. For gauged catchments, flood frequency analysis can be used to estimate design floods; however, for ungauged catchments, regional flood frequency analysis (RFFA) is used. This paper compares two popular RFFA techniques, namely the quantile regression technique (QRT) and the index flood method (IFM). A total of 181 catchments are selected for this study from south-east Australia. Eight predictor variables are used to develop prediction equations. It has been found that IFM outperforms QRT in general. For higher annual exceedance probabilities (AEPs), IFM generally demonstrates a smaller estimation error than QRT; however, for smaller AEPs (e.g. 1 in 100), QRT provides more accurate quantile estimates. The IFM provides comparable design flood estimates with the Australian Rainfall and Runoff—the national guide for design flood estimation in Australia.

Suggested Citation

  • Amir Zalnezhad & Ataur Rahman & Farhad Ahamed & Mehdi Vafakhah & Bijan Samali, 2023. "Design flood estimation at ungauged catchments using index flood method and quantile regression technique: a case study for South East Australia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 119(3), pages 1839-1862, December.
    • Handle: RePEc:spr:nathaz:v:119:y:2023:i:3:d:10.1007_s11069-023-06184-7
    DOI: 10.1007/s11069-023-06184-7
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    References listed on IDEAS

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    1. Ayesha Rahman & Ataur Rahman & Mohammad Zaman & Khaled Haddad & Amimul Ahsan & Monzur Imteaz, 2013. "A study on selection of probability distributions for at-site flood frequency analysis in Australia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(3), pages 1803-1813, December.
    2. Pezhman Allahbakhshian-Farsani & Mehdi Vafakhah & Hadi Khosravi-Farsani & Elke Hertig, 2020. "Regional Flood Frequency Analysis Through Some Machine Learning Models in Semi-arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2887-2909, July.
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